The prevalence, diversity, and economic value of electronic commerce have increased dramatically as Internet use has grown. Retailers that participate in this electronic commerce often do so by maintaining a website for potential customers to view and purchase goods and services. Accordingly, studying the way people interact with retail websites can yield important insights about how to attract customers and close sales. This interest in electronic commerce, specifically web-based sales, has led to the development of web analytics, which is the study of Internet data derived from users interacting with webpages.
The Internet data used for web analytics may be provided by computers in a numerical or tabular form, such as in a web server log file that records transactions that occurred on a web server. However, the raw data presented in this numerical or tabular form may be difficult for people to interpret. Therefore, various techniques for displaying this data in a visual or graphical form have been developed. However, the visualization techniques developed thus far are not able to show interactions between customers and websites with sufficient clarity and detail. Some visualization techniques suffer from oversimplification in which important details are not presented graphically while other visualizations are overly complex and difficult to interpret.